Dolutegravir, a second-generation integrase strand transfer inhibitor (InSTI), is replacing efavirenz as first-line antiretroviral therapy (ART) in low middle-income countries (LMICs). Tuberculosis remains the leading cause of HIV-related morbidity and mortality in LMICs. Rifampicin is a key agent in the treatment of tuberculosis but induces genes involved in dolutegravir metabolism and efflux. The resulting drug-drug interaction (DDI) reduces the exposure of dolutegravir. However, this can be overcome by supplying a supplemental dose of 50 mg dolutegravir 12 hours after the standard daily dose, which is difficult to implement in LMICs. Four lines of evidence suggest that the supplemental dose may not be necessary 1) a phase 2 study showed 10 mg of dolutegravir as effective as 50 mg; 2) the prolonged dissociative half-life of dolutegravir after binding to its receptor; 3) a DDI study reported dolutegravir trough concentrations were maintained above its minimum effective concentration when using 50 mg dolutegrssed throughout. Trial registrations clinicaltrials.gov NCT03851588 (22/02/2019), SANCTR DOH-27-072020-8159 (03/07/2020).Background The assessment of the severity and case fatality rates of coronavirus disease 2019 (COVID-19) and the determinants of its variation is essential for planning health resources and responding to the pandemic. The interpretation of case fatality rates (CFRs) remains a challenge due to different biases associated with surveillance and reporting. For example, rates may be affected by preferential ascertainment of severe cases and time delay from disease onset to death. Using data from Spain, we demonstrate how some of these biases may be corrected when estimating severity and case fatality rates by age group and gender, and identify issues that may affect the correct interpretation of the results. Methods Crude CFRs are estimated by dividing the total number of deaths by the total number of confirmed cases. CFRs adjusted for preferential ascertainment of severe cases are obtained by assuming a uniform attack rate in all population groups, and using demography-adjusted under-ascertainment rates. CFRs adjusted for the delay between disease onset and death are estimated by using as denominator the number of cases that could have a clinical outcome by the time rates are calculated. A sensitivity analysis is carried out to compare CFRs obtained using different levels of ascertainment and different distributions for the time from disease onset to death. Results COVID-19 outcomes are highly influenced by age and gender. Different assumptions yield different CFR values but in all scenarios CFRs are higher in old ages and males. Conclusions The procedures used to obtain the CFR estimates require strong assumptions and although the interpretation of their magnitude should be treated with caution, the differences observed by age and gender are fundamental underpinnings to inform decision-making.Heart failure (HF) is a common cause of hospitalization and mortality in older adults. HF is almost always embedded within a larger pattern of multimorbidity, yet many studies exclude patients with complex psychiatric and medical comorbidities or cognitive impairment. This has left significant gaps in research on the problems and treatment of patients with HF. In addition, HF is only one of multiple challenges facing patients with multimorbidity, stressful socioeconomic circumstances, and psychosocial problems. The purpose of this study is to identify combinations of comorbidities and health disparities that may affect HF outcomes and require different mixtures of medical, psychological, and social services to address. The syndemics framework has yielded important insights into other disorders such as HIV/AIDS, but it has not been applied to the complex psychosocial problems of patients with HF. The multimorbidity framework is an alternative approach for investigating the effects of multiple comorbidities on health outcomes. The specific aims are (1) to determine the coprevalence of psychiatric and medical comorbidities in patients with HF (n = 535); (2) to determine whether coprevalent comorbidities have synergistic effects on readmissions, mortality, self-care, and global health; (3) to identify vulnerable subpopulations of patients with HF who have high coprevalences of syndemic comorbidities; (4) to determine the extent to which syndemic comorbidities explain adverse HF outcomes in vulnerable subgroups of patients with HF; and (5) to determine the effects of multimorbidity on readmissions, mortality, self-care, and global health.Brain and Neuroscience Advances has grown in tandem with the British Neuroscience Association's campaign to build Credibility in Neuroscience, which encourages actions and initiatives aimed at improving reproducibility, reliability and openness. This commitment to credibility impacts not only what the Journal publishes, but also how it operates. With that in mind, the Editorial Board sought the views of the neuroscience community on the peer review process, and on how they should respond to the Journal Impact Factor that will be assigned to Brain and Neuroscience Advances. https://www.selleckchem.com/products/mm3122.html In this editorial, we present the results of a survey of neuroscience researchers conducted in the autumn of 2020 and discuss the broader implications of our findings for the Journal and the neuroscience community.Humans and non-human animals show great flexibility in spatial navigation, including the ability to return to specific locations based on as few as one single experience. To study spatial navigation in the laboratory, watermaze tasks, in which rats have to find a hidden platform in a pool of cloudy water surrounded by spatial cues, have long been used. Analogous tasks have been developed for human participants using virtual environments. Spatial learning in the watermaze is facilitated by the hippocampus. In particular, rapid, one-trial, allocentric place learning, as measured in the delayed-matching-to-place variant of the watermaze task, which requires rodents to learn repeatedly new locations in a familiar environment, is hippocampal dependent. In this article, we review some computational principles, embedded within a reinforcement learning framework, that utilise hippocampal spatial representations for navigation in watermaze tasks. We consider which key elements underlie their efficacy, and discuss their limitations in accounting for hippocampus-dependent navigation, both in terms of behavioural performance (i.